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Hybrid Fuzzy Controller Based Frequency Regulation in Restructured Power System  [PDF]
P. Anitha, P. Subburaj
Circuits and Systems (CS) , 2016, DOI: 10.4236/cs.2016.76065
Abstract: This paper discusses the implementation of Load Frequency Control (LFC) in restructured power system using Hybrid Fuzzy controller. The formulation of LFC in open energy market is much more challenging; hence it needs an intelligent controller to adapt the changes imposed by the dynamics of restructured bilateral contracts. Fuzzy Logic Control deals well with uncertainty and indistinctness while Particle Swarm Optimization (PSO) is a well-known optimization tool. Abovementioned techniques are combined and called as Hybrid Fuzzy to improve the dynamic performance of the system. Frequency control of restructured system has been achieved by automatic Membership Function (MF) tuned fuzzy logic controller. The parameters defining membership function has been tuned and updated from time to time using Particle Swarm Optimization (PSO). The robustness of the proposed hybrid fuzzy controller has been compared with conventional fuzzy logic controller using performance measures like overshoot and settling time following a step load perturbation. The motivation for using membership function tuning using PSO is to show the behavior of the controller for a wide range of system parameters and load changes. Error based analysis with parametric uncertainties and load changes is tested on a two-area restructured power system.
mplementation of Load Frequency Control of Hydrothermal System under Restructured Scenario Employing Fuzzy Controlled Genetic Algorithm  [PDF]
DR.C.SRINIVASA RAO
International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering , 2013,
Abstract: This paper presents the implementation of load frequency control (LFC) of hydrothermal system under restructured scenario employing fuzzy controlled genetic algorithm (FCGA). The concept of artificial intelligent techniques greatly helps in overcoming the disadvantages posed by the conventional controllers. Open transmission access and the evolving of more socialized companies for generation, transmission and distribution affects the formulation of LFC problem. So the traditional LFC system is modified to take into account the effect of bilateral contracts on the dynamics. Fuzzy logic is a powerful tool for dealing with imprecision and uncertainty while Genetic Algorithm is a potential tool for global optimization. A combinedtechnique involving both these techniques called as fuzzy controlled genetic algorithm has been developed to remove the limitations of these techniques and also improve the dynamic performance of the system over the existing conventional techniques. Simulation results show that the system employing fuzzy controlled genetic algorithm has better dynamic performance over the system with traditional integral controller.
Electric Distribution System Planning by Distributed Generators Installing in Restructured Power Market  [cached]
F. Gharedaghi,H. Jamali,M. Deisi,A. Khalili
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: The large number of decision variables of long-term planning problem for improving the distribution system causes lots of complexities. The optimum allocation of Distributed Generation (DG) sources and determining their capacity in the deregulated electric market is a key way for capacity expansion of the distribution firm. In this study, a new approach is presented to determination the optimum location and capacity of DG sources in the deregulated electric market through the net present value analysis using an optimization model. This model aims to minimize the investment cost of the distribution firm, utility cost and the losses cost considering the anticipated load peak value. Considering the power market price anticipation to be indefinite, the proposed method is based on laying out the genetic algorithm and a fuzzy model to the power market price and the capacity expansion design of the distribution system during different time intervals is proposed along with two static and semi-dynamic methods. The efficiency of the proposed approach is well shown applying it to a sample network.
Load frequency control of an asynchronous restructured power system: a fuzzy logic approach
SK Pandey, SP Singh, VP Singh
International Journal of Engineering, Science and Technology , 2012,
Abstract: This paper presents the analysis of load frequency control (LFC) of a two-area restructured power system interconnected via parallel ac/dc transmission links. Simulation results show that the limitations of PI controller can be overcome by including Fuzzy logic concept and thereby the dynamic performance can be improved substantially following a load change in any area. The dynamic responses for small perturbation have been observed with PI controller and fuzzy logic based PI controller and result of both have been compared.
Optimized Self Scheduling of Power Producers in a Restructured Power Market  [cached]
S. Torabzad,B. Ojaghi,M. Davudi
Research Journal of Applied Sciences, Engineering and Technology , 2012,
Abstract: Generation scheduling and dispatch are determined by individual power producers’ bids in a deregulated power market. The benefits obtained by a power producer will depend largely on how effectively it can incorporate the variation of the market price in its generation scheduling. This paper addresses the selfscheduling problem and design of optimal bidding strategy for a price-taker company. By restructuring the electric power systems, market participants are facing an important task of bidding energy to an Independent System Operator (ISO). This study proposes a model and a method for optimization-based bidding and selfscheduling where a utility bids part of its energy and self-schedules the rest. The model considers ISO bid selections and uncertain bidding information of other market participants. With appropriately simplified bidding and ISO models, closed-form ISO solutions are first obtained. These solutions are then plugged into the utility’s bidding and self-scheduling model which is solved by using Lagrangian relaxation. Testing results depicts that the method has effective solutions with acceptable computation time.
Intelligent User Interface in Fuzzy Environment  [PDF]
Ben Khayut,Lina Fabri,Maya Abukhana
Computer Science , 2014,
Abstract: Human-Computer Interaction with the traditional User Interface is done using a specified in advance script dialog menu, mainly based on human intellect and unproductive use of navigation. This approach does not lead to making qualitative decision in control systems, where the situations and processes cannot be structured in advance. Any dynamic changes in the controlled business process (as example, in organizational unit of the information fuzzy control system) make it necessary to modify the script dialogue in User Interface. This circumstance leads to a redesign of the components of the User Interface and of the entire control system. In the Intelligent User Interface, where the dialog situations are unknown in advance, fuzzy structured and artificial intelligence is crucial, the redesign described above is impossible. To solve this and other problems, we propose the data, information and knowledge based technology of Smart/ Intelligent User Interface (IUI) design, which interacts with users and systems in natural and other languages, utilizing the principles of Situational Control and Fuzzy Logic theories, Artificial Intelligence, Linguistics, Knowledge Base technologies and others. The proposed technology of IUI design is defined by multi-agents of Situational Control and of data, information and knowledge, modelling of Fuzzy Logic Inference, Generalization, Representation and Explanation of knowledge, Planning and Decision-making, Dialog Control, Reasoning and Systems Thinking, Fuzzy Control of organizational unit in real-time, fuzzy conditions, heterogeneous domains, and multi-lingual communication under uncertainty and in Fuzzy Environment.
Applicability of Crisp and Fuzzy Logic in Intelligent Response Generation  [PDF]
T. V. Prasad,Sachin Lakra,G. Ramakrishna
Computer Science , 2012,
Abstract: This paper discusses the merits and demerits of crisp logic and fuzzy logic with respect to their applicability in intelligent response generation by a human being and by a robot. Intelligent systems must have the capability of taking decisions that are wise and handle situations intelligently. A direct relationship exists between the level of perfection in handling a situation and the level of completeness of the available knowledge or information or data required to handle the situation. The paper concludes that the use of crisp logic with complete knowledge leads to perfection in handling situations whereas fuzzy logic can handle situations imperfectly only. However, in the light of availability of incomplete knowledge fuzzy theory is more effective but may be disadvantageous as compared to crisp logic.
Application of fuzzy cognitive map in information intelligent push
Application of fuzzy cognitive map in information intelligent push
 [PDF]

张佳,徐胜利,邓方
- , 2015, DOI: 10.15918/j.jbit1004-0579.201524.0419
Abstract: Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required information. Information intelligent push technology could replace the traditional method to speed up the information retrieval process. The fuzzy cognitive map has strong knowledge representation ability and reasoning capability. Information intelligent push with the basis on fuzzy cognitive map could abstract the computer user's operations to a fuzzy cognitive map, and infer the user's operating intentions. The reasoning results will be translated into operational events, and drive the computer system to push appropriate information to the user.
Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required information. Information intelligent push technology could replace the traditional method to speed up the information retrieval process. The fuzzy cognitive map has strong knowledge representation ability and reasoning capability. Information intelligent push with the basis on fuzzy cognitive map could abstract the computer user's operations to a fuzzy cognitive map, and infer the user's operating intentions. The reasoning results will be translated into operational events, and drive the computer system to push appropriate information to the user.
Fuzzy Clustering in an Intelligent Agent for Diagnosis Establishment
Zdrenghea Vlad,Iuliu Hategan,Man Diana Ofelia,Tosa-Abrudan Maria
Scientific Bulletin of the ''Petru Maior" University of T?rgu Mure? , 2009,
Abstract: In this paper we present a way to use fuzzy clustering for generating fuzzy rule bases in the implementation of an intelligent agent that interacts with human for diagnosis establishment: The (Psychiatric) Medical Diagnostics System. The system is intended to be a software learning application mainly destined to orientate the resident doctors in the process of establishing a diagnostic for the patients theyare examining.Learning techniques have been used for clustering and to form the premise portion of the If-Then rules. The general idea is to generate a set of fuzzy rules that not only best describe the data at hand but also are robust enough to show good generalization capabilities.
Fuzzy queries in romanian language an intelligent interface
Cornelia TUDORIE,Cristian NEACSU,Ionel MANOLACHE
Annals of Dunarea de Jos , 2005,
Abstract: The most accessible interfaces querying databases must be so intelligent, able to understand natural language expressions and including vague terms in selection criteria. The paper proposes a general architecture for a flexible database interface and also a real implementation of such a system. It is general enough, so it can be connected to any database, after a specific knowledge base description. The natural language processing is mainly based on lexico-syntagmatical analyse; the vague criteria interpreting and evaluating are based on the fuzzy logic.
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